Research Communications Manager Jobs

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values. Truveta was born in the Pacific Northwest in the USA and has employees who live across the country. As we expand our global footprint with a new presence in Hyderabad, India, we’re building a world-class team to help us scale this mission and Clinical Intelligence and AI Evaluation is at the heart of everything we do. This job requires daily onsite work at our headquarters in Hyderabad, India. Who We Need Truveta is rapidly building a talented and diverse team to tackle complex health and technical challenges. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you. This Opportunity At Truveta, we believe that high data quality will play a critical role in accomplishing our mission towards saving lives with data. An important component of this work is data normalization in which the medical terminology linking, and terminology management are essential in building deep intelligence empowering the new generation of clinical research. We are looking for a full-time Clinical Terminologist who will help to standardize the data sourced from different health systems. The responsibilities include identifying, creating, or validating mapping between medical terms from various healthcare system to standardized Terminologies

The Lead - Strategy is responsible for driving strategic initiatives, decision-making frameworks, and feasibility assessments for various projects within NMDPL. This role involves extensive research, stakeholder engagement, financial modeling, and charter development to support informed decision-making. The role will oversee project visibility, product mix strategies, industrial resettlement, and financial planning while ensuring alignment with business objectives and stakeholder expectations. Source: Adani Group | Job ID: 50810

Clinical Team Lead (Registered Nurse) 📍 Wales – Multi‑Site Role (Travel Across Wales Required) 💷 £29.14 – £37.50 per hour 🩺 Community‑based | Flexible shifts | Weekly pay Pulse is recruiting registered nurses for a Clinical Team Lead role supporting Our Future Health , the UK’s largest health research programme. This is a mobile, multi‑site role across Wales , ideal for nurses who enjoy variety, autonomy, and working across different community locations. The role is suitable for experienced Band 6/7 nurses , or Band 5 nurses with leadership or supervisory experience who are ready to step up into a clinical leadership position. Nurses who are flexible to travel across multiple sites will be particularly well suited. This is a nurse‑led, patient‑facing leadership role , where you’ll provide day‑to‑day clinical oversight while remaining hands‑on within community clinic environments. ✅ Band 5 nurses with acting‑up, mentoring, or shift‑lead experience are strongly encouraged to apply ✅ Induction, shadowing and ongoing support provided About the role You will lead and support Healthcare Assistants and Phlebotomists delivering health screening clinics as part of Our Future Health . Clinics operate across South, West, Mid and North Wales. You’ll play a key role in ensuring safe, high‑quality care , a positive participant experience, and consistent standards across sites. Flexibility to travel between locations will allow you to maximise available shifts and variety in your work. Locations available South East Wales (including Newport, Cwmbran, Pontypool, Caerphilly, Penarth, Barry, Chepstow, Abergavenny) South Wales Valleys (including Talbot Green, Tonypandy) Swansea Bay & Carmarthenshire (including Port Talbot, Neath, Llanelli, Carmarthen) West Wales (including Haverfordwest, Milford Haven, Pembroke) Mid Wales (including Aberystwyth, Newtown) North West Wales (including Bangor, Caernarfon, Porthmadog, Holyhead) North East Wales (including Rhyl, C

About the Team DoorDash is seeking a seasoned Engineering Director to lead our Logistics Org. You’ll lead a multi-disciplinary organization of 100+ engineers (Backend, Mobile, Machine Learning, and Operations Research) to architect the intelligent, real-time systems that comprise the "brain" of our fulfillment engine. This organization builds the optimization engines and high-throughput AI platforms that guide millions of Dashers and deploy tens of millions of dollars in real-time. This team sits at the heart of DoorDash’s fulfillment ecosystem, powering the delivery and courier data that drives our logistics engine. We build the foundational models and workflows that enable our customer teams (Order, Shopping, and beyond) to build extensible solutions on top of the platform. About the Role DoorDash is seeking a Director of Engineering with a deep background in Large-Scale Systems, Machine Learning, and Mathematical Optimization to lead our Logistics team in San Francisco. In this role, you are the architect of our three-sided marketplace. You will oversee the development of the core fulfillment platforms responsible for real-time dispatching, dynamic pricing task-allocation, ETAs and supply-demand balancing. This is a unique opportunity to marry complex algorithmic research with "five-nines" platform reliability. We are also looking for a leader who is deeply bought into the transformative potential of AI; someone who sees large language models, foundation models, and world model architectures not as adjacent curiosities but as core primitives for reimagining how logistics systems learn, plan, and adapt at scale. You’re excited about this opportunity because you will… Define the AI & Platform Vision: Drive the engineering strategy, transitioning bespoke algorithmic solutions into a unified, scalable AI/Optimization platform. Architect Real-Time Decision Engines: Lead the development of systems that solve complex combinatorial problems (VRP, assignment, pricing)

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Threat Intelligence team protects OpenAI’s technology, people, research, and infrastructure by proactively identifying and disrupting adversaries who seek to compromise our systems or misuse our models. We investigate sophisticated threats, build tooling to scale and augment analysis, and deliver intelligence that shapes security strategy and equips leadership with timely, risk-aware insights. We combine technical depth, investigative rigor, and strong cross-functional partnerships to uncover threats and drive impact across OpenAI’s security and research organizations. About the Role As a Technical Threat Investigator at OpenAI, you will help protect the company from sophisticated adversaries targeting OpenAI and the broader ecosystem, as well as those attempting to misuse our models in support of cyber operations. This is a deeply investigative role. You will independently conduct complex, end-to-end investigations into capable threat actors to understand their behavior, infrastructure, emerging techniques, and how AI is integrated into their workflows. You’ll use these insights to proactively identify malicious activity and drive detection, disruption, enforcement, and safety improvements across the company. You’ll translate your investigative findings into durable solutions that scale impact. You’ll build and own lightweight tooling, automate where it matters, and create AI-assisted workflows to make investigations faster, more repeatable, and more effective over time. In this role, you will: Conduct deep, end-to-end investigations into sophisticated threat actors interacting with OpenAI’s models, products, and broader ecosystem. Think like an adversary — model attacker behavior, anticipate misuse patterns, and proactively hunt for, identify, and disrupt malicious activity. Leverage internal telemetry, OSINT, vendor data, a

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Our Fraud team's mission is to help companies detect and prevent fraud using Plaid's financial network data. We believe that transaction patterns, device signals, identity linkages, and behavioral data are dramatically underleveraged tools in fraud prevention. Our products — including Protect and Signal — operate at network scale and depend on real-world investigation and research to stay ahead of adaptive adversaries. As a Fraud Intelligence Analyst, you will sit at the intersection of live fraud investigation, applied data science, and product innovation. You will lead complex investigations, translate findings into detection improvements, and collaborate tightly with Data Science, ML, and Product teams to shape the next generation of Plaid's fraud capabilities. This is not a purely operational role — your research directly drives features, model inputs, and product design. Responsibilities: Live Fraud Investigation & Reconstruction Lead investigations into complex fraud cases across identities, accounts, devices, and transaction surfaces Provide support to day-to-day fraud operations including SEVs and alert triage Reconstruct attacker sequences and hypothesize actor intent

About Zencoder At Zencoder.ai , we build and orchestrate AI agents that ship real work - code, research, operations, and more. What started as developer tooling is becoming a platform where people and agents collaborate across knowledge work tasks. The Opportunity We're looking for an experienced engineer to raise the bar on how our organization builds, tests, ships, and operates software - for both human engineers and AI coding agents. This is AI harness engineering: the discipline of making the fundamentals (CI/CD, testing, IaC, observability, secure delivery) so solid and well-shaped that agents can work productively inside them. Developer experience and platform engineering are a subset of that work. When the harness is good, humans ship faster and agents stop getting stuck on things that shouldn't be hard. Security is inseparable from this. AI agents are accelerating both the pace and the shape of vulnerabilities, and secure delivery has to be built into the same stream as everything else - not bolted on. Product teams own their services, pipelines, and tests. Your job is to raise the ceiling across the org - defining standards, building leverage, and helping teams level up their workflows, tooling, infrastructure, security posture, and necessary changes to get the most out of coding agents. Key Responsibilities This is a hands-on lead role - you'll be deep in the code, infra, and pipelines yourself. Shape the platform and infrastructure that everything else runs on - the foundations product teams build on top of; Improve the full developer loop: local development, remote agents, CI/CD, deployment, observability; Build shared tooling, templates, and golden paths that create real leverage - paved roads teams actually want to use; Stay ahead of the shifting security landscape as AI agents reshape both how vulnerabilities emerge and how they're exploited. Essential Qualifications Strong software engineering background - you will be building both tooling and

Frontier AI labs decide what direction their models need to take before the actual training starts. As a Senior Frontier Data Strategist on Scale's Generative AI team, you'll be a trusted voice in those decisions. You'll partner with research leads and senior stakeholders at the world's leading AI labs to shape the data strategy behind their next generation of models, then design the human-data programs to deliver it. You'll sit where frontier research meets Scale's product roadmap, and you'll be expected to move both. With customers, you'll own senior, technically grounded relationships, anticipate where their research is heading, and bring them new data ideas before they ask. Inside Scale, you'll be a leading voice with our AI Product Managers, ML Research, Delivery Operations, and Engagement Management teams, turning what you learn from customers into product priorities and investment decisions. This is a forward-looking, highly cross-functional role. Our Engagement Managers own customer success for live programs; Frontier Data Strategists own everything that comes before it: spotting the need, designing the program, scoping and forecasting it, and winning the work. As a senior member of the team, you'll set the standard for how Scale does this work and help develop the Frontier Data Strategists around you. What you’ll do: Own relationships with senior research stakeholders at your assigned frontier labs, such as research leads, heads of post-training, and technical leadership, and become a strategic thought partner on their post-training, evaluation, and agent roadmaps. Set the data strategy for your accounts: anticipate needs across research areas, spot where the biggest opportunities are, and build a multi-program plan for how Scale can help. Direct the cross-functional team designing Scale's most complex and novel human-data programs, including work that has no precedent at Scale. Shape Scale's product roadmap by representing your customers in planning with A

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions optimized for advanced AI workloads. We collaborate across research, software, and external hardware partners to design and deploy next-generation AI systems at scale. Our team works closely with silicon vendors and system partners to evaluate emerging technologies, validate performance characteristics, and ensure that hardware capabilities translate effectively to real-world AI workloads. About the Role We are seeking a 3P Hardware Architecture Expert with deep expertise in GPU and accelerator architectures to engage directly with silicon vendors and guide hardware decisions for AI infrastructure. In this role, you will evaluate architectural tradeoffs across compute, memory, and interconnect systems, translating vendor specifications into real-world workload impact. You will play a critical role in early silicon evaluation, benchmarking, and performance validation, helping ensure that next-generation hardware meets the needs of our workloads. This role is highly hands-on and requires both deep technical understanding and the ability to engage at a high level with partners such as NVIDIA and AMD on architectural direction and design tradeoffs. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance. Key Responsibilities Engage deeply with silicon vendors (e.g NVIDIA & AMD) on GPU and accelerator architecture tradeoffs. Analyze and interpret performance, power, and efficiency characteristics of next-generation hardware. Translate vendor specifications into expected real-world performance for AI workloads. Evaluate architectural aspects including: compute throughput and utilization memory systems (HBM, cache hierarchies, bandwidth constraints) data types and precision tradeoffs (FP16, BF16, FP8, etc.) interconnect and scaling behavior. Run benchmarks and profiling to validate hardware performance a

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with research, software, and external hardware partners to shape the next generation of AI systems, from silicon through full-scale deployments. Our team focuses on understanding and optimizing performance across the full system stack—ensuring that architectural decisions are grounded in rigorous, quantitative analysis of real-world workloads. About the Role We are seeking a Performance Modeling Lead to build and lead a small, high-impact team responsible for answering forward-looking architectural questions across AI infrastructure systems. You will develop modeling frameworks and methodologies to evaluate system-level tradeoffs and guide key design decisions. Your work will directly influence reference architectures, vendor designs, and long-term infrastructure strategy. This role sits at the intersection of AI workloads, system architecture, and quantitative modeling, and requires strong technical judgment, ownership, and the ability to translate complex analysis into clear, actionable guidance. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance. Key Responsibilities Build and own a performance modeling framework/toolchain to evaluate AI systems across multiple levels of abstraction. Analyze and quantify architectural tradeoffs across compute, memory, networking, storage, and system topology. Develop performance models to guide decisions on: scale-up vs. scale-out architectures interconnect and network design memory hierarchy and system balance. Translate modeling outputs into clear recommendations for internal teams and external hardware vendors. Influence reference designs and vendor roadmaps through data-driven insights. Partner closely with machine learning, systems, and hardware teams to understand workload characte

About the Team Safety Systems manages the complete lifecycle of safety efforts for OpenAI’s frontier models, ensuring our models are deployed responsibly and have a positive impact on society. Our work spans diverse research and engineering initiatives—from system-level safeguards and model training to evaluation and red-teaming—all aimed at mitigating misuse and maintaining our high bar for safety. We lead OpenAI's commitment to developing and deploying safe Artificial General Intelligence (AGI), fostering a culture of trust, responsibility, and transparency. Our goal is to continuously learn from deployments, distribute AI’s benefits widely, and ensure that powerful tools remain aligned with human values and safety considerations. About the Role The Safety Measurement Product Manager owns OpenAI's approach to measuring harm and safeguard efficacy in production, including driving the strategy for our suite of safety measurement platforms and products used across the company. You will partner closely with our safety research and engineering teams to determine what we measure, where we measure it, and how we measure it, feeding those insights directly into critical leadership decisions and back into our safety work. You will also represent the company's topline safety metric as well as prioritize incoming requests from partner teams to expand our safety measurement platform to more use cases. This position is based in San Francisco, CA, with relocation assistance available. In this role, you will: Partner closely with data science, research, engineering, policy teams, and other stakeholders to craft a vision for understanding safety outcomes and prevalence on our platforms. Define strategic priorities and product roadmaps focused on improving safety measurement approaches will scaling our measurement platform to more use cases, products, and cross-functional team needs. Establish repeatable processes to integrate cutting-edge AI safety research into OpenAI’s safety m

Datadog is seeking a Director of Product Management to lead our AI Observability portfolio and shape how organizations build, monitor, and scale AI systems in production. This role leads LLM Observability and helps define the next wave of innovation across GPU Monitoring, Distributed AI Monitoring, and emerging research-oriented tooling such as Model Lab. You will set the vision and strategy for this rapidly growing area, expanding established products while incubating new capabilities that deliver deep visibility into AI infrastructure, model performance, and distributed AI environments. As AI becomes core to modern applications, this team plays a critical role in ensuring customers can deploy and scale AI with confidence. We’re looking for a builder-minded product leader with strong technical depth and hands-on curiosity - someone who has built or worked closely with AI-powered products and understands the realities of production AI. You will lead a team of product managers and partner closely with engineering and design to advance Datadog’s leadership in AI observability. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the vision and strategy for AI-driven products, ensuring alignment with overall company goals and customer needs. This will include managing our embed program to enhance the capabilities of existing products as well as developing dedicated and independent AI products. Lead and mentor a team of product managers, helping them grow and advance their careers while ensuring the delivery of high-quality, AI-powered features. Collaborate with cross-functional teams including engineering, data science, marketing, and sales to deliver AI product solutions that meet customer needs and business objectives. Identify new opportunities for

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for applied AI engineers to help bring Codex agents from impressive demos to dependable tools. This role is about improving agent performance on real software engineering tasks and closing the gap between research capability and real-world usefulness. You’ll work closely with research, infrastructure, and product to ensure agents are not just powerful, but useful, steerable, and reliable in practice. The job is not only to improve model behavior in isolation, but to turn those improvements into measurable gains in solve rate, usefulness, and economic value for users. What You’ll Do Design and iterate on agent behaviors across real-world coding tasks and long-horizon workflows. Work closely with research to develop and run evals to measure agent performance, regressions, failure modes, and edge cases. Improve performance through prompting, tool-use strategies, context construction, and model-facing experimentation. Analyze failures in production and systematically improve robustness and reliability. Build feedback loops and data systems that get better real-task data into evaluation and research. Work with product teams to shape user-facing agent experiences and the interfaces the agent depends on. Help define what “good” looks like for agents completing complex tasks end-to-end. You Might Be a Good Fit If You Ha

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for engineers to build the infrastructure that powers Codex agents in production. This role focuses on the systems that let models safely execute code, interact with tools, complete long-running tasks, and operate reliably and efficiently at scale. You’ll design and operate the infrastructure behind sandboxed execution, orchestration, stateful workflows, app-server and SDK boundaries, and model rollouts. You’ll work at the intersection of distributed systems, developer tooling, and AI, building primitives that make Codex faster, safer, more reliable, and easier for the rest of the organization to build on. What You’ll Do Design and build execution environments for AI agents, including sandboxing, isolation, and reproducibility. Develop systems for agent orchestration across multi-step, tool-using workflows. Build infrastructure for running, testing, and debugging code generated by models. Create state and memory systems that allow agents to persist context across long-running tasks. Optimize tokens, latency, reliability, and cost across Codex’s production fleet. Support model rollouts, capacity planning, and the core tradeoffs between quality, speed, and economics to manage a fleet of frontier agents at scale. Build shared platform capabilities that unblock product teams, partner teams, and open source Codex. Yo

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Role Snorkel AI is hiring a Director, Forward Deployed Researcher on the Data-as-a-service team. Your team will partner directly with frontier AI labs on their hardest data problems: scoping training data needs, designing RL environments, developing evaluation frameworks, and translating customer research objectives into actionable technical plans. This is a player-coach role. Roughly half your time goes to people leadership (hiring, coaching, developing your team) and the other half to hands-on technical work on strategic accounts. You set the technical bar for spec quality and build the playbooks and processes that let the team scale. You influence how the function operates, from process and standards to team culture. You partner closely with AE leadership on pipeline strategy, account coverage, and SE allocation. You also work cross-functionally with Delivery, Research, and Engineering to ensure smooth handoffs. The right person for this role can hold their own with frontier AI researchers, has strong presales instincts, and wants to build a team. Main Responsibilities Recruit, hire, and develop the forward deployed research team, coaching the team on technical quality, customer engagement, and career growth Set and maintain the technical bar for specifications, evaluation frameworks, and customer deliverables Own SE capacity planning and account coverage; partner with AE leadership on deal strategy, engagement prioritization, and pipeline